MilaNLProc/survey-language-technologies huggingface dataset:
Gender: Female 
Age: 45-54
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Divorced 
First language: English 
Religion: Christian 
Education: High school or below
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 5
Home: Rent 
Employment: Employed full time
Occupation: Clerical support workers (those who perform clerical duties such as organizing, storing, computing and retrieving information)
Mother's occupation: Clerical support workers (those who perform clerical duties such as organizing, storing, computing and retrieving information)
Father's occupation: Technicians and associate professionals (those who apply scientific or artistic concepts and operational methods, e.g. secretaries, fitness workers, lab technicians)
Hobbies: Exercise;Use social media;Attend football matches;Watch sports 
Devices used daily: Laptop;Smartphone;Smartwatch 
NLP tools known: Grammar checker (i.e., correcting grammar mistakes);Spell checker (i.e., correcting misspellings) 
NLP tools used: Grammar checker (i.e., correcting grammar mistakes);Dialog technology (e.g. chatbots that communicate with you such as chatGPT) 
NLP tools they would find useful: Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text) 
Frequency of LLM use: Rarely
LLMs used: ChatGPT 
Contexts of LLM use: Work;Personal 
Prompt 1: “Why would you like to be part of the Pathfinders program, how you demonstrate and live our values and why you should be selected”.
Prompt 2: What are the differences in roles between a senior account manager and account manager?
Prompt 3: Summarise what a synopsis is in GCSE food and technology?
Comments: No comments on survey, but on Chat Bots, I have found these to be useful on the limited times I have used them.
Gender: Female 
Age: 25-34
Nationality: United Kingdom
Ethnicity: Black or African American 
Marital status: Cohabitating 
First language: English 
Religion: Christian 
Education: Graduate degree
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 3
Home: Rent 
Employment: Employed part time
Occupation: Service and sales workers (whose who provide personal and protective services related to travel, housekeeping, catering, personal care, protection against fire and unlawful acts)
Mother's occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations)
Father's occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations)
Hobbies: Use social media;Exercise;Go to gigs 
Devices used daily: Laptop;Smartphone 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
NLP tools used: Spell checker (i.e., correcting misspellings);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder) 
NLP tools they would find useful: Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Sentiment analysis (e.g. automatically detect if user reviews are positive or negative)Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Text-to-Speech (i.e, computers being able to read out loud written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
Frequency of LLM use: Nearly every day
LLMs used: ChatGPT;Snapchat My AI 
LLM use cases: Translation;Brainstorming;Solving math or logical problems;Learning (e.g., explaining complex concepts in simple terms);Summarizing long texts 
Contexts of LLM use: Learning 
Prompt 1: chatgbt
Prompt 2: snapchatai
Prompt 3: metaai
Prompt 4: whatappai
Prompt 5: google ai
Comments: none for now
Gender: Female 
Age: 45-54
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Cohabitating 
First language: English 
Religion: Christian 
Education: Graduate degree
Mother's education: Prefer not to say
Father's education: Prefer not to say
Self-assessed socioeconomic status (1-10): 5
Home: Own 
Employment: Employed full time
Occupation: Clerical support workers (those who perform clerical duties such as organizing, storing, computing and retrieving information)
Mother's occupation: Service and sales workers (whose who provide personal and protective services related to travel, housekeeping, catering, personal care, protection against fire and unlawful acts)
Father's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Hobbies: Listen to jazz;Listen to rock/indie music;Do arts and crafts;Watch sports 
Devices used daily: Laptop 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Speech-to-Text (i.e. a computer transcribing your spoken language to written language) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Dialog technology (e.g. chatbots that communicate with you such as chatGPT) 
NLP tools they would find useful: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
Frequency of LLM use: Nearly every day
LLMs used: ChatGPT 
LLM use cases: Coding;Writing (e.g., composing emails);Generic chatbot conversation;Analyze data;Answering questions about general knowledge 
Contexts of LLM use: Work;Personal 
Prompt 1: how do i access bank account
Prompt 2: when is the doctor avaiilable
Prompt 3: what time is the action to be completed
Prompt 4: Please name some relaxation techniques
Prompt 5: How can I pacify my child
Prompt 6: What vitamins are needed
Prompt 7: Unable to access report why
Prompt 8: What the timescales needed
Prompt 9: What order should the file be upload
Prompt 10: What transfer needs to be done and when
Comments: no
Gender: Female 
Age: 60+
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Married 
First language: English 
Religion: Nothing 
Education: High school or below
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 5
Home: Own 
Employment: Retired
Occupation: Homemaker
Mother's occupation: Homemaker
Father's occupation: Craft related trades workers (those who produce or process foodstuffs, textiles, wooden, metal and other articles, including handicraft goods, and apply specific technical and practical knowledge and skills to construct and maintain buildings)
Hobbies: Other (Please specify) meals out, watch television
Devices used daily: Smartphone;Tablet;Smartwatch 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder) 
NLP tools they would find useful: Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Speech-to-Text (i.e. a computer transcribing your spoken language to written language) 
Frequency of LLM use: Rarely
LLMs used: ChatGPT 
LLM use cases: Writing (e.g., composing emails);Get information about current events 
Prompt 1: when is the best time to book a cruise
Prompt 2: what can I cook with leftover pork
Prompt 3: write me a standard complaint letter about the coverage on my mobile phone
Gender: Male 
Age: 35-44
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Single 
First language: English 
Religion: Nothing 
Education: Undergraduate degree
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 6
Home: Own 
Employment: Employed full time
Occupation: Clerical support workers (those who perform clerical duties such as organizing, storing, computing and retrieving information);Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations)
Mother's occupation: Clerical support workers (those who perform clerical duties such as organizing, storing, computing and retrieving information)
Father's occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations)
Hobbies: Listen to classical music;Listen to rock/indie music;Attend football matches;Watch sports;Use social media 
Devices used daily: Laptop;Smartphone 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Sentiment analysis (e.g. automatically detect if user reviews are positive or negative)Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT) 
NLP tools they would find useful: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT) 
Frequency of LLM use: Rarely
LLMs used: ChatGPT 
LLM use cases: Writing (e.g., composing emails) 
Contexts of LLM use: Work 
Prompt 1: Write an email template for sending to a customer who is late paying an invoice. Formal and respectful tone.
Gender: Male 
Age: 60+
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Married 
First language: English 
Religion: Christian 
Education: Undergraduate degree
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 6
Home: Own 
Employment: Retired
Occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Mother's occupation: Elementary occupations (jobs that involve simple and routine tasks which may require the use of hand-held tools and considerable physical effort)
Father's occupation: Plant and machine operators, and assemblers (those who maintain, operate and monitor industrial and agricultural machinery and equipment)
Hobbies: Listen to rock/indie music;Watch sports;Exercise 
Devices used daily: Laptop;Smartphone;Tablet 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);Dialog technology (e.g. chatbots that communicate with you such as chatGPT) 
NLP tools used: Spell checker (i.e., correcting misspellings);Dialog technology (e.g. chatbots that communicate with you such as chatGPT) 
NLP tools they would find useful: Speech-to-Text (i.e. a computer transcribing your spoken language to written language) 
Frequency of LLM use: Rarely
LLMs used: ChatGPT 
LLM use cases: Brainstorming;Generic chatbot conversation 
Contexts of LLM use: Personal 
Prompt 1: Write a limerick about a 3 1/2 mile coastal hike near Whitby. Must include names: Frank, Louise, Andy, Lea
Prompt 2: A limerick about Flamboyant Oscar, who is 23, and whisky
Prompt 3: Write a limerick about Mike who is 57 today
Prompt 4: Write a limerick about the difference between free verse and assonance
Prompt 5: Write a limerick about Bobby - who has never used Chat GPT
Prompt 6: A limerick about Bobby, who never threw any old things away
Prompt 7: Write me a limerick about a dog called Buddy wanting England to win the Euro 2024 finals
Prompt 8: Why has the song "Sweet Caroline" been adopted by England football fans?
Prompt 9: I have thousands of holiday photos. I want to take the best of them and put them into a sort of album that I then make into a movie. I use a mac computer and I don't want to spend money on specialist software. What are my best options?
Prompt 10: What foods are beneficial to my skin?
Comments: All good.
Gender: Male 
Age: 18-24
Nationality: United Kingdom;Nigeria
Ethnicity: Black or African American 
Marital status: Single 
First language: English 
Religion: Christian 
Education: Undergraduate degree
Mother's education: Undergraduate degree
Father's education: Undergraduate degree
Self-assessed socioeconomic status (1-10): 5
Home: Rent 
Employment: Employed part time
Occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Mother's occupation: Clerical support workers (those who perform clerical duties such as organizing, storing, computing and retrieving information)
Father's occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations)
Hobbies: Listen to classical music;Listen to hiphop and rap;Exercise;Attend football matches 
Devices used daily: Laptop;Smartphone 
NLP tools known: Grammar checker (i.e., correcting grammar mistakes);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language);Dialog technology (e.g. chatbots that communicate with you such as chatGPT) 
NLP tools used: Text-to-Speech (i.e, computers being able to read out loud written language);Dialog technology (e.g. chatbots that communicate with you such as chatGPT) 
NLP tools they would find useful: Grammar checker (i.e., correcting grammar mistakes);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language) 
Frequency of LLM use: Every day
LLMs used: ChatGPT;Grok;Snapchat My AI 
LLM use cases: Coding;Writing (e.g., composing emails);Generic chatbot conversation;Solving math or logical problems 
Contexts of LLM use: Creative or artistic;Work;Learning 
Prompt 1: What is the meaning of neurodivergent
Prompt 2: Help me create a bio for a social media account called "Lyrics On A Roll"
Prompt 3: Explain in detail the difference between fahrenheit and celsius
Prompt 4: Compare music and Poetry
Prompt 5: develop a function that calculates the power of a number using recursion. Make it an input
Prompt 6: DatetimeIndex.format is deprecated and will be removed in a future version. Convert using index.astype(str) or index.map(formatter) instead.
Prompt 7: How to upgrade cufflinks in my terminal
Prompt 8: Create a data frame for clients with the values ranging from 200,000 to 500,000   inclusive to be displayed for the last  12 months (from January to December), considering 31 days in each month
Prompt 9: How do I build a website that has an algorithm that predicts forex market results and create trading signals for traders
Prompt 10: In a case where two ssl certificates are mistakenly used on one domain, if I want to take out the ssl certificate and add it to a new domain, how do I do that
Gender: Male 
Age: 18-24
Nationality: United States
Ethnicity: Black or African American 
Marital status: Single 
First language: English 
Religion: Christian 
Education: Undergraduate degree
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 5
Home: Rent 
Employment: Employed part time
Occupation: Technicians and associate professionals (those who apply scientific or artistic concepts and operational methods, e.g. secretaries, fitness workers, lab technicians)
Mother's occupation: Service and sales workers (whose who provide personal and protective services related to travel, housekeeping, catering, personal care, protection against fire and unlawful acts)
Father's occupation: Elementary occupations (jobs that involve simple and routine tasks which may require the use of hand-held tools and considerable physical effort)
Hobbies: Listen to jazz;Go to gigs;Other (Please specify) read
Devices used daily: Laptop;Smartphone;Smartwatch 
NLP tools known: Grammar checker (i.e., correcting grammar mistakes);Spell checker (i.e., correcting misspellings);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Speech-to-Text (i.e. a computer transcribing your spoken language to written language) 
NLP tools used: Grammar checker (i.e., correcting grammar mistakes);Spell checker (i.e., correcting misspellings);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants) 
NLP tools they would find useful: Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language) 
Frequency of LLM use: Nearly every day
LLMs used: ChatGPT;GitHub Copilot 
LLM use cases: Coding;Paraphrasing or finding synonyms;Proofreading/Editing (e.g., grammar, spelling, structure improvements);Analyze data;Learning (e.g., explaining complex concepts in simple terms);Answering questions about general knowledge;Summarizing long texts;Get information about current events 
Contexts of LLM use: Work;School/University;Learning;Personal;Technical 
Prompt 1: top 10 books about financial intelligence and management 
Prompt 2: add more
Prompt 3: as recommended by warren buffet
Prompt 4: what are digital twins in technology?
Prompt 5: air bnb
Prompt 6: How did Canada respond to Donald Trump’s threat to impose 25% tariffs on all Canadian products?
Prompt 7: Oce gold mining in new Zealand. Can't recall the name but can you help out
Prompt 8: what does it imply when a patient have a blood pressure is 106
Prompt 9: Give me a full list of Australian Universities providing post graduate studies in data science
Prompt 10: For the list given or other universities add the scholarship funding for international studies and add the links to their respective sites.
Gender: Male 
Age: 60+
Nationality: United States
Ethnicity: Black or African American 
Marital status: Married 
First language: English 
Religion: Christian 
Education: Graduate degree
Mother's education: Graduate degree
Father's education: Graduate degree
Self-assessed socioeconomic status (1-10): 5
Home: Own 
Employment: Employed full time
Occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Mother's occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations)
Father's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Hobbies: Listen to classical music;Attend football matches;Watch sports 
Devices used daily: Laptop;Smartphone 
NLP tools known: Spell checker (i.e., correcting misspellings);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Speech-to-Text (i.e. a computer transcribing your spoken language to written language) 
NLP tools used: E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Spell checker (i.e., correcting misspellings) 
NLP tools they would find useful: Text-to-Speech (i.e, computers being able to read out loud written language) 
Frequency of LLM use: Nearly every day
LLMs used: ChatGPT;Google Gemini;Meta Llama 2 
LLM use cases: Coding;Translation;Writing (e.g., composing emails);Proofreading/Editing (e.g., grammar, spelling, structure improvements);Solving math or logical problems;Analyze data;Completing assignments 
Contexts of LLM use: Learning;Work 
Prompt 1: What is the current unemployment rate?
Prompt 2:  Who made the decision about what to do with Andy's life support machinery?
Prompt 3: Who made the prognosis for Andy?
Prompt 4: Do you think the junior physician did what was right?
Prompt 5:  Was Andy's life support turned off?
Prompt 6: Who made the prognosis for Andy in the short story you just read?
Prompt 7: What is the current inflation rate in the US?
Prompt 8: What are the causes of morning cough?
Prompt 9: What is the best treatment for morning cough?
Prompt 10: What is the first anouncement President Trump made after his inauguration? 
Comments: None
Gender: Male 
Age: 45-54
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Divorced 
First language: English 
Religion: Buddhist 
Education: Undergraduate degree
Mother's education: Undergraduate degree
Father's education: Graduate degree
Self-assessed socioeconomic status (1-10): 2
Home: Other (Please specify) live with parents
Employment: Self-employed full time
Occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Mother's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Father's occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations)
Hobbies: Other (Please specify) motox
Devices used daily: Laptop;Smartphone 
NLP tools known: Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language);Spell checker (i.e., correcting misspellings) 
NLP tools used: Spell checker (i.e., correcting misspellings);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants) 
NLP tools they would find useful: Spell checker (i.e., correcting misspellings);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants) 
Frequency of LLM use: Never
Comments: I do not use AI. I dislike it and believe that its biased in what the programmer wants.  I do not trust the main stream media and believe there is an agenda against us. Therefore I do not use GPT etc. My work tries to encourage using it but I believe I can cope perfectly well without it.
Gender: Female 
Age: 18-24
Nationality: United Kingdom
Ethnicity: Black or African American 
Marital status: Cohabitating 
First language: English 
Religion: Christian 
Education: Graduate degree
Mother's education: High school or below
Father's education: Undergraduate degree
Self-assessed socioeconomic status (1-10): 6
Home: Rent 
Employment: Employed full time
Occupation: Plant and machine operators, and assemblers (those who maintain, operate and monitor industrial and agricultural machinery and equipment)
Mother's occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations)
Father's occupation: Technicians and associate professionals (those who apply scientific or artistic concepts and operational methods, e.g. secretaries, fitness workers, lab technicians)
Hobbies: Go to gigs;Use social media;Exercise;Listen to hiphop and rap 
Devices used daily: Laptop;Smartphone 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Dialog technology (e.g. chatbots that communicate with you such as chatGPT) 
NLP tools they would find useful: Spell checker (i.e., correcting misspellings);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Dialog technology (e.g. chatbots that communicate with you such as chatGPT) 
Frequency of LLM use: Nearly every day
LLMs used: ChatGPT;Claude;Character.AI 
LLM use cases: Translation;Writing (e.g., composing emails);Proofreading/Editing (e.g., grammar, spelling, structure improvements);Generic chatbot conversation;Learning (e.g., explaining complex concepts in simple terms);Summarizing long texts;Get information about current events 
Contexts of LLM use: Work;School/University;Learning;Personal 
Prompt 1: "Can you help me write a poem about the ocean?"
Prompt 2: "What's the capital of Madagascar?
Prompt 3: "Give me a recipe for a vegan lasagna."
Prompt 4: "Can you explain quantum physics in simple terms?"
Prompt 5: "What's the meaning of life?"
Prompt 6: "Write a short story where a cat becomes president."
Prompt 7: "How do I deal with stress at work?"
Prompt 8: "Tell me a fun fact about space."
Prompt 9: "Translate 'Good morning' into Japanese."
Prompt 10: "What are the best strategies for improving memory retention?"
Comments: Thank you.
Gender: Male 
Age: 18-24
Nationality: United States
Ethnicity: Black or African American 
Marital status: Married 
First language: English 
Religion: Christian 
Education: Graduate degree
Mother's education: Doctorate or above
Father's education: Doctorate or above
Self-assessed socioeconomic status (1-10): 10
Home: Rent 
Employment: Employed full time
Occupation: Technicians and associate professionals (those who apply scientific or artistic concepts and operational methods, e.g. secretaries, fitness workers, lab technicians)
Mother's occupation: Skilled agricultural, forestry and fishery workers (those harvest, grow, breed, or produce a variety of animal husbandry products)
Father's occupation: Armed forces occupations (includes all jobs held by members of the armed forces)
Hobbies: Listen to hiphop and rap 
Devices used daily: Laptop 
NLP tools known: Dialog technology (e.g. chatbots that communicate with you such as chatGPT);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Grammar checker (i.e., correcting grammar mistakes);Spell checker (i.e., correcting misspellings) 
NLP tools used: Sentiment analysis (e.g. automatically detect if user reviews are positive or negative)Machine translation (e.g. translate Chinese or Russian into English, and vice versa) 
NLP tools they would find useful: Grammar checker (i.e., correcting grammar mistakes) 
Frequency of LLM use: Rarely
LLMs used: ChatGPT 
LLM use cases: Coding;Writing (e.g., composing emails);Paraphrasing or finding synonyms 
Contexts of LLM use: Personal;Work;School/University 
Prompt 1: Can you explain the latest advancements in artificial intelligence?
Prompt 2: What are some tips for improving time management skills?
Prompt 3: How can I increase my productivity while working from home?
Prompt 4: Can you recommend some good books on personal development?
Prompt 5: What are some effective strategies for improving mental health?
Prompt 6: How does quantum computing work and why is it important?
Prompt 7: Can you suggest some sustainable practices for reducing waste at home?
Prompt 8: What are the best methods for learning a new language quickly?
Prompt 9: How do I optimize my social media privacy settings?
Prompt 10: What are some common myths about nutrition and health?
Gender: Male 
Age: 35-44
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Cohabitating 
First language: English 
Religion: Nothing 
Education: High school or below
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 4
Home: Other (Please specify) With family
Employment: Not employed, but looking for work
Occupation: Prefer not to say
Mother's occupation: Prefer not to say
Father's occupation: Prefer not to say
Hobbies: Listen to classical music;Other (Please specify) PC gaming, reading, cooking
Devices used daily: Laptop;Smartphone;Other PC
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Sentiment analysis (e.g. automatically detect if user reviews are positive or negative)Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Sentiment analysis (e.g. automatically detect if user reviews are positive or negative)Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
Frequency of LLM use: Sometimes
LLMs used: ChatGPT;Claude;Other Copilot
LLM use cases: Coding;Translation;Generic chatbot conversation;Solving math or logical problems;Analyze data;Learning (e.g., explaining complex concepts in simple terms) 
Contexts of LLM use: Personal 
Comments: I cannot gather chat history as none are appearing when I visit the relevant chatbots.
Gender: Male 
Age: 25-34
Nationality: United Kingdom
Ethnicity: Black or African American 
Marital status: Married 
First language: English 
Religion: Christian 
Education: Graduate degree
Mother's education: Graduate degree
Father's education: Graduate degree
Self-assessed socioeconomic status (1-10): 5
Home: Own 
Employment: Employed full time
Occupation: Technicians and associate professionals (those who apply scientific or artistic concepts and operational methods, e.g. secretaries, fitness workers, lab technicians)
Mother's occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations)
Father's occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations)
Hobbies: Listen to classical music 
Devices used daily: Smartphone 
NLP tools known: Dialog technology (e.g. chatbots that communicate with you such as chatGPT) 
NLP tools used: Text-to-Speech (i.e, computers being able to read out loud written language) 
NLP tools they would find useful: Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Text-to-Speech (i.e, computers being able to read out loud written language) 
Frequency of LLM use: Sometimes
LLM use cases: Translation;Writing (e.g., composing emails) 
Contexts of LLM use: Personal
Gender: Female 
Age: 25-34
Nationality: United States
Ethnicity: White / Caucasian 
Marital status: Married 
First language: English 
Religion: Muslim 
Education: Graduate degree
Mother's education: Graduate degree
Father's education: Graduate degree
Self-assessed socioeconomic status (1-10): 10
Home: Rent 
Employment: Employed full time
Occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations)
Mother's occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations)
Father's occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations)
Hobbies: Listen to jazz 
Devices used daily: Laptop 
NLP tools known: E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder) 
NLP tools used: E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder) 
NLP tools they would find useful: E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder) 
Frequency of LLM use: Rarely
LLMs used: ChatGPT 
LLM use cases: Writing (e.g., composing emails) 
Contexts of LLM use: Work;Learning
Gender: Male 
Age: 18-24
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Single 
First language: English 
Religion: Nothing 
Education: Undergraduate degree
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 4
Home: Rent 
Employment: Student
Occupation: Prefer not to say
Mother's occupation: Service and sales workers (whose who provide personal and protective services related to travel, housekeeping, catering, personal care, protection against fire and unlawful acts)
Father's occupation: Craft related trades workers (those who produce or process foodstuffs, textiles, wooden, metal and other articles, including handicraft goods, and apply specific technical and practical knowledge and skills to construct and maintain buildings)
Hobbies: Use social media 
Devices used daily: Smartphone 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language) 
NLP tools used: Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants) 
NLP tools they would find useful: Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text) 
Frequency of LLM use: Never
Gender: Male 
Age: 35-44
Nationality: United States
Ethnicity: White / Caucasian 
Marital status: Cohabitating 
First language: English 
Religion: Prefer not to say 
Education: High school or below
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 1
Home: Rent 
Employment: Not employed, but looking for work
Occupation: Service and sales workers (whose who provide personal and protective services related to travel, housekeeping, catering, personal care, protection against fire and unlawful acts);Plant and machine operators, and assemblers (those who maintain, operate and monitor industrial and agricultural machinery and equipment)
Mother's occupation: Service and sales workers (whose who provide personal and protective services related to travel, housekeeping, catering, personal care, protection against fire and unlawful acts)
Father's occupation: Plant and machine operators, and assemblers (those who maintain, operate and monitor industrial and agricultural machinery and equipment)
Hobbies: Go to gigs;Watch sports;Listen to rock/indie music 
Devices used daily: Laptop;Smartphone 
NLP tools known: Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Spell checker (i.e., correcting misspellings);Text-to-Speech (i.e, computers being able to read out loud written language);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Speech-to-Text (i.e. a computer transcribing your spoken language to written language) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder) 
NLP tools they would find useful: Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
Frequency of LLM use: Never
Gender: Female 
Age: 35-44
Nationality: United Kingdom
Ethnicity: Black or African American 
Marital status: Married 
First language: English 
Religion: Christian 
Education: Undergraduate degree
Mother's education: Graduate degree
Father's education: Undergraduate degree
Self-assessed socioeconomic status (1-10): 7
Home: Rent 
Employment: Employed part time
Occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Mother's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Father's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Hobbies: Use social media 
Devices used daily: Smartphone 
NLP tools known: Spell checker (i.e., correcting misspellings);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Grammar checker (i.e., correcting grammar mistakes);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Dialog technology (e.g. chatbots that communicate with you such as chatGPT) 
NLP tools used: Grammar checker (i.e., correcting grammar mistakes);Spell checker (i.e., correcting misspellings);Text-to-Speech (i.e, computers being able to read out loud written language);Dialog technology (e.g. chatbots that communicate with you such as chatGPT) 
NLP tools they would find useful: E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Grammar checker (i.e., correcting grammar mistakes);Spell checker (i.e., correcting misspellings);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
Frequency of LLM use: Every day
LLMs used: ChatGPT;Character.AI;Snapchat My AI 
LLM use cases: Translation;Writing (e.g., composing emails);Summarizing long texts;Answering questions about general knowledge 
Contexts of LLM use: Learning;Personal 
Prompt 1: What's the weather like today
Prompt 2: Can you help me write a cover letter for a job application?
Prompt 3: How do I make a homemade pizza dough?
Prompt 4: Can you summarize the latest news
Prompt 5: What are some good books to read 
Prompt 6: Can you explain how quantum computing works?
Prompt 7: What are the best strategies for managing time effectively?
Prompt 8: Help me brainstorm ideas for a new business venture.
Prompt 9: Can you recommend a good movie to watch tonight?
Prompt 10: How do I convert pounds to naira?
Gender: Female 
Age: 55-60
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Married 
First language: English 
Religion: Christian 
Education: Undergraduate degree
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 6
Home: Own 
Employment: Employed full time
Occupation: Clerical support workers (those who perform clerical duties such as organizing, storing, computing and retrieving information)
Mother's occupation: Homemaker
Father's occupation: Plant and machine operators, and assemblers (those who maintain, operate and monitor industrial and agricultural machinery and equipment)
Hobbies: Go to gigs;Visit to stately homes;Exercise;Use social media;Go to museums and galleries 
Devices used daily: Laptop;Tablet;Smartphone 
NLP tools known: Spell checker (i.e., correcting misspellings);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Speech-to-Text (i.e. a computer transcribing your spoken language to written language) 
NLP tools used: Spell checker (i.e., correcting misspellings);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants) 
Frequency of LLM use: Sometimes
LLMs used: ChatGPT 
LLM use cases: Translation;Get information about current events 
Contexts of LLM use: Entertainment;Learning 
Prompt 1: Where is luxembourg 
Prompt 2: How long is a flight to luxembourg 
Prompt 3: How old is madonna
Prompt 4: How do I make toad in the hole
Prompt 5: Where has the best weather in the uk
Prompt 6: How do I wire a plug
Prompt 7: What is the theory of relativity 
Prompt 8: What is quantum mechanics
Gender: Male 
Age: 60+
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Single 
First language: English 
Religion: Nothing 
Education: High school or below
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 3
Home: Rent 
Employment: Not employed, but looking for work
Occupation: Plant and machine operators, and assemblers (those who maintain, operate and monitor industrial and agricultural machinery and equipment)
Mother's occupation: Elementary occupations (jobs that involve simple and routine tasks which may require the use of hand-held tools and considerable physical effort)
Father's occupation: Elementary occupations (jobs that involve simple and routine tasks which may require the use of hand-held tools and considerable physical effort)
Hobbies: Use social media;Watch sports 
Devices used daily: Laptop;Smartphone 
NLP tools known: Spell checker (i.e., correcting misspellings);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Grammar checker (i.e., correcting grammar mistakes) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants) 
NLP tools they would find useful: Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Text-to-Speech (i.e, computers being able to read out loud written language);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text) 
Frequency of LLM use: Never
Comments: no